Optimizing Spatial Relationships in GCN to Improve the Classification Accuracy of Remote Sensing Images

Semantic segmentation of remote sensing images is one of the core tasks of remote sensing image interpretation.With the continuous develop-ment of artificial intelligence technology,the use of deep learning methods for interpreting remote-sensing images has matured.Existing neural networks disregard the spatial relationship between two targets in remote sensing images.Semantic segmentation models that combine convolutional neural networks(CNNs)and graph convolutional neural networks(GCNs)cause a lack of feature boundaries,which leads to the unsatisfactory segmentation of various target feature boundaries.In this paper,we propose a new semantic segmentation model for remote sensing images(called DGCN hereinafter),which combines deep semantic segmentation networks(DSSN)and GCNs.In the GCN module,a loss function for boundary information is employed to optimize the learning of spatial relationship features between the target features and their relationships.A hierarchical fusion method is utilized for feature fusion and classification to optimize the spatial relationship informa-tion in the original feature information.Extensive experiments on ISPRS 2D and DeepGlobe semantic segmentation datasets show that compared with the existing semantic segmentation models of remote sensing images,the DGCN significantly optimizes the segmentation effect of feature boundaries,effectively reduces the noise in the segmentation results and improves the segmentation accuracy,which demonstrates the advancements of our model.

Evolution of Jobs-housing Spatial Relationship in Beijing Metropolitan Area:A Job Accessibility Perspective

With the urban expansion and economic restructuring, the jobs-housing relationship has become an important issue in studies on urban spatial structure. This paper employed a job accessibility model, which is an evaluation instrument to measure the jobs-housing relationship in Beijing Metropolitan Area from a job accessibility perspective. The results indicate that the population in the central city is declining, whereas the population in the suburbs is consistently growing and forming new population centers. However, the distribution pattern of employment is still highly centralized. Job accessibility varies in different locations, but the inner-city areas(within the Third Ring road) have seen improved job accessibility over time while job accessibility in the suburbs(especially outside the Fourth Ring road) has decreased, and this has led it to become a primary area of residential and employment mismatch. At the same time, the new towns in the outer suburbs have not yet demonstrated great potential to attract more jobs. In addition we find that, to some extent, urban planning changes the jobs-housing relationship, but a polycentric urban spatial structure is not yet evident. The floating population and related housing policy also affect the jobs-housing relationship. We propose some measures to resolve the spatial mismatch as well as some future research directions.

The new multistage water adsorption model of Longmaxi Formation shale considering the spatial configuration relationship between organic matter and clay minerals

The water adsorption by shale significantly affects shale gas content and its seepage capacity.However,the mechanism of water adsorption by shale is still unclear due to its strong heterogeneity and complicated pore structure.The relationship between the adsorbed water content at different relative humidities(RHs)and shale compositions,as well as shale pore structure and the spatial configuration relationship between organic matter(OM)and clay minerals,was investigated to clarify the controlling factors and mechanisms of water adsorption by Longmaxi Formation shale from the Southern Sichuan Basin in China.Consequently,the water adsorption process could be generally divided into three different stages from 0%RH to 99%RH.Furthermore,the Johnston’s clay mine ral interlayer pore structure model(JCM),the Freundlich model(FM)and the Dubinin-Astakhov model(DAM)were tested to fit the three water adsorption stages from low RH to high RH,respectively.The fitting results of the JCM and FM at lower RHs were far from good,while the fitting results of DAM at higher RHs were acceptable.Accordingly,two revised models(LRHM and MRHM)considering the spatial configuration relationship between OM and clay minerals were proposed for the two stages with lower RHs,and performed better fitting results indicating the pronounced effect of the spatial configuration relationship between OM and clay minerals on the water adsorption process of Longmaxi Formation shale.The outcomes of this study will contribute to clarifying the water distribution characteristics in the pore network of shale samples with variable water contents.

Multi-scale spatial relationships between soil total nitrogen and influencing factors in a basin landscape based on multivariate empirical mode decomposition

The relationships between soil total nitrogen(STN)and influencing factors are scale-dependent.The objective of this study was to identify the multi-scale spatial relationships of STN with selected environmental factors(elevation,slope and topographic wetness index),intrinsic soil factors(soil bulk density,sand content,silt content,and clay content)and combined environmental factors(including the first two principal components(PC1 and PC2)of the Vis-NIR soil spectra)along three sampling transects located at the upstream,midstream and downstream of Taiyuan Basin on the Chinese Loess Plateau.We separated the multivariate data series of STN and influencing factors at each transect into six intrinsic mode functions(IMFs)and one residue by multivariate empirical mode decomposition(MEMD).Meanwhile,we obtained the predicted equations of STN based on MEMD by stepwise multiple linear regression(SMLR).The results indicated that the dominant scales of explained variance in STN were at scale 995 m for transect 1,at scales 956 and 8852 m for transect 2,and at scales 972,5716 and 12,317 m for transect 3.Multi-scale correlation coefficients between STN and influencing factors were less significant in transect 3 than in transects 1 and 2.The goodness of fit root mean square error(RMSE),normalized root mean square error(NRMSE),and coefficient of determination(R2)indicated that the prediction of STN at the sampling scale by summing all of the predicted IMFs and residue was more accurate than that by SMLR directly.Therefore,the multi-scale method of MEMD has a good potential in characterizing the multi-scale spatial relationships between STN and influencing factors at the basin landscape scale.

Image Retrieval Based on Objects’ Spatial Orientation Relationships

A new concept of characteristic scanning radial (CSR) is proposed for thesegmented image on the basis of two shape-specific points of its shape-objects. Subsequently, twocharacteristic attribute sequences (CAS) of relative distance and relative direction are derived torepresent the spatial orientation relationships among objects of the image. A novel image retrievalalgorithm is presented using these two CASs. The proposed retrieval approach not only satisfies thetransformational invariance, butalso attains the quantitative comparison of matching. Experimentsidentify the effectiveness and efficiency of the algorithm adequately.

Spatial coupling relationships of gas hydrate formation in the Tibetan Plateau

At present, gas hydrates are known to occur in continental high latitude permafrost regions and deep sea sediments. For middle latitude permafrost regions of the Tibetan Plateau, further research is required to ascertain its potential development of gas hydrates. This paper reviewed pertinent literature on gas hydrates in the Tibetan Plateau. Both geological and ge- ographical data are synthesized to reveal the relationship between gas hydrate formation and petroleum geological evo- lution, Plateau uplift, formation of permafrost, and glacial processes. Previous studies indicate that numerous residual basins in the Plateau have been formed by original sedimentary basins accompanied by rapid uplift of the Plateau. Ex- tensive marine Mesozoic hydrocarbon source rocks in these basins could provide rich sources of materials forming gas hydrates in permafrost. Primary hydrocarbon-generating period in the Plateau is from late Jurassic to early Cretaceous, while secondary hydrocarbon generation, regionally or locally, occurs mainly in the Paleogene. Before rapid uplift of the Plateau, oil-gas reservoirs were continuously destroyed and assembled to form new reservoirs due to structural and thermal dynamics, forcing hydrocarbon migration. Since 3.4 Ma B.P., the Plateau has undergone strong uplift and extensive gla- ciation, periglacier processes prevailed, hydrocarbon gas again migrated, and free gas beneath ice sheets within sedi- mentary materials interacted with water, generating gas hydrates which were finally preserved under a cap formed by frozen layers through rapid cooling in the Plateau. Taken as a whole, it can be safely concluded that there is great temporal and spatial coupling relationships between evolution of the Tibetan Plateau and generation of gas hydrates.

PHYLETIC RELATIONSHIP OF PROTEIN STRUCTURES BASED ON SPATIAL PREFERENCE OF RESIDUES

A distance measure that infers to indicate the evolutionary relationship of protein structures has been developed based on spatial preference factors of residues. The spatial preference factor is a reflection of the environment of residues in tertiary structure. Compared with the phyletic relationships derived from sequence homologies and three-dimensional structures, we find that the two lines of evolution are similar in general. This approach is applied to a group of glins here.

Two new approaches for image registration based onspatial-temporal relationship

How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.

“外察”与“内省”:环境威胁引发的绿色消费意愿研究——基于道德情绪的双路径模型

营销学者在探究绿色消费议题方面做了众多开创性工作,然而针对诱因不同的环境威胁是否及通过怎样的心理路径影响消费者绿色消费意愿的研究仍然匮乏。本文将环境威胁分为自然因素引发的环境威胁和人为因素引发的环境威胁两类,通过4组实验检验了两类环境威胁影响消费者绿色消费意愿的心理机制。研究结果证实了无论哪类环境威胁,都会对绿色产品购买行为产生积极影响,但不同类型的环境威胁会通过差异化认知过程和情绪反应影响绿色产品购买行为。当消费者面对自然因素引发的环境威胁时,其“外察”思维模式会起主导作用,此时敬畏感是促进绿色产品购买意愿的中介变量;当消费者面对人为因素引发的环境威胁时,其“内省”思维模式会起主导作用,此时内疚感是促进绿色产品购买意愿的中介变量。研究也证实了环境威胁对道德情绪的影响会受自然联结性和道德提升感的调节。

An efficient selectivity estimation method for spatial query optimization with topological relationships

Many commercial database systems maintain histograms to summarize the contents of relations and permit the efficient estimation of query result sizes and the access plan cost. In spatial database systems, most spatial query predicates are consisted of topological relationships between spatial objects, and it is very important to estimate the selectivity of those predicates for spatial query optimizer. In this paper, we propose a selectivity estimation scheme for spatial topological predicates based on the multi dimensional histogram and the transformation scheme. Proposed scheme applies two partition strategy on transformed object space to generate spatial histogram and estimates the selectivity of topological predicates based on the topological characteristics of the transformed space. Proposed scheme provides a way for estimating the selectivity without too much memory space usage and additional I/Os in most spatial query optimizers.

要素流动对城乡融合发展的影响机理与空间分异研究

城乡要素双向自由流动有利于提高要素配置效率和优化城乡关系,促进城乡融合发展。现有关于要素流动对城乡融合发展的研究主要围绕传统生产要素对城乡融合发展的研究展开讨论,鲜有文献将数据这一新型生产要素纳入城乡要素流动范围并探索其对城乡融合发展的影响机理。基于2010—2021年中国31个省份的面板数据,在测算要素流动、城乡融合发展水平的基础上,构建双向固定效应模型、地理加权回归模型和中介效应模型实证检验要素流动对城乡融合发展的影响效应及作用机制。研究发现:第一,全国要素流动总指数呈现出小幅度增长的态势,位于均值之上的地区中64%是城乡融合发展试验区,说明城乡融合发展政策实施具有重要的引导作用;第二,要素流动显著促进城乡融合发展,这一结论在引入城乡之间距离作为工具变量进行内生性检验、采用删除4个直辖市和缩短时间窗口的方法进行稳健性检验之后仍然成立;第三,空间异质性分析中,劳动力、土地和数据要素始终表现出促进城乡融合发展的作用,随着时间的推移,土地要素对不同地区城乡融合发展影响程度逐渐增强、影响范围逐步扩大,技术要素对城乡融合发展的促进逐渐凸现,由华东和华南地区向东北和西南地区转移;第四,在要素流动影响城乡融合发展的过程中,电商销售是要素流动影响城乡融合发展的重要途径,农业机械化和产业结构变迁并未发挥出中介变量的作用,不同于已有的研究结果。因此,今后持续深化城乡融合发展的内涵与外延、拓展深度与广度;始终以习近平新时代中国特色社会主义思想为指导,运用科学的世界观和方法论,坚持整体推进与试点示范相统一的指导原则,推广实践中形成的典型经验。研究结论为城乡要素双向合理流动的机制建立、城乡融合发展体制机制的健全提供了理论和经验上的参考。

SPATIAL OBJECTS AND SPATIAL RELATIONSHIPS

Spatial object and spatial relationship are two basic concepts of GIS.Spatial object is the digital representation of geographical entity or phenomenon,which forms the basis for data management and analysis;spatial relationship is theconnexion between spatial objects when geometric properties are considered.Thecommonly used classification of spatial objects as points,lines and areas is mathe-matically strict,and suitable for data management,but a bit too generalized forrepresenting real entities and extracting spatial relationships.A good classificationmodel should not only be good for representing real entities,but also good for re-vealing spatial relationships,therefore good for formalizing spatial analyses.

绿色基础设施供需适配关系演进特征及其规律--以南京市为例

绿色基础设施(GI)供需均衡对维护城市或区域生态系统稳定,提升国土空间治理体系和治理能力现代化水平,推动城市高质量发展具有重要意义。从绿色基础设施供需适配关系的视角出发,运用生态系统服务价值法对GI服务供给进行测度,从社会、经济、生态和环境四方面综合评价GI需求,研究南京市GI供需适配关系的演进情势,揭示其时空配置的差异性。结果表明:(1)2000—2020年,南京市GI供给呈主城低、郊区高的分布格局,总供给、人均供给和单项供给均先减后增。(2)GI总需求逐年减少,形成从中心城区向郊区递减的三个圈层。(3)南京市共划出9个供需适配类型,对应11个辖区划出99个供需适配类型组合区,供需适配较好区与较差区分别占全市国土面积的26%和44%,呈不均衡分布。(4)主城区较适应的匹配类型是低供给-中需求,郊区维持低供给-低需求较符合区域发展实际,并针对不同类型区优化提升提出对策建议。

海洋观视角下海洋城市发展的历史回顾与国际比较

海洋观是人类在生产生活中对海洋的总体认识,随着海洋科技与国际关系发展而持续演变,为厘清不同历史时期海洋城市的差异特征提供了重要的研究视角。基于文献综述与类型归纳相结合的方法,重点关注海洋观变迁下全球典型海洋城市发展的空间演变与发展趋势。研究发现,在殖民、后殖民、全球化海洋观演变过程中,海洋城市职能从早期的贸易型逐渐转变为产业型与服务型,其战略属性主要体现为在全球、区域与国家多维空间尺度下的连通性、撬动性与支撑性。应充分发挥海洋城市战略属性,面向世界级海洋城市群开展现代海洋城市建设。

空间视域下思想政治教育一体化的概念、内容及建设

社会发展和社会变迁深刻影响着空间格局,空间成为解析社会现象、反映社会思想观念变化的重要理论和实践场域。空间与社会的互动使人的发展、社会的发展空间趋向合理化,使空间变革愈加富有社会化特质。人的思想观念、情感体验、行为实践、社会关系在一定的空间当中被塑造和完善,空间在思想政治教育一体化的作用下逐渐具有思想政治教育意蕴。在阐释空间视域下思想政治教育一体化的概念、分析其内容的基础上提出空间视域下思想政治教育一体化建设思路和举措:实现社会主流意识形态的广泛传播,在对空间的占有当中筑牢思想政治教育一体化的基础;掌握变革社会的力量,通过对空间主体的培养塑造凝聚思想政治教育一体化的主体力量;促进人与社会关系的和谐,通过对空间关系的协调把握思想政治教育一体化的关键。

基于混合智能的街景影像知识提取方法

针对街景影像目标的智能化提取难题,本文提出了一种基于混合智能的街景影像知识提取方法(K-CAPSNet)。首先,在现有全景分割网络的基础上,同时关注街景影像的通道信息和空间信息,发展了一种联合注意力机制的全景分割网络,以提高目标分割精度;其次,将人们在生产、生活中形成的街景知识融入街景影像认知过程,借助先验知识设置目标标记阈值,对分割结果进行优化;然后,进一步根据街景影像先验知识验证街景目标之间的拓扑关系并利用深度信息进行空间关系知识挖掘;最后,采用语义模板对街景目标类型、数量及空间关系进行描述和表达。试验表明,相较于基线网络,本文方法在全景分割质量和识别质量方面都有明显提升,较好地实现了对街景影像知识的提取与表达。

明代《弇山园记》中的意象单元结构关系及空间营造研究

弇山园是晚明第一名园,其园林空间营造具有模块化、组团化的特征。先对王世贞《弇山园记》中的意象单元进行提取并完成空间单元的图示化转译,以求更清晰地展现每个意象单元所呈现的具体空间特征及意境营造。其次运用“解离—重构”的研究方法,完成“意象单元、空间单元、空间组团”这一园林系统的建构,进而实现对弇山园意象单元结构关系及空间营造的研究。该研究对于明代园林的传承借鉴以及当代的景观设计具有重要意义,亦为古典园林空间研究提供了新思路。

东北地区城镇化与资源环境承载力耦合关系的时空变化

理清城镇化与资源环境承载力耦合关系可为城市可持续发展转型提供决策参考。在分析2003—2019年东北地区城镇化与资源环境承载力时空格局的基础上,采用耦合协调度模型定量剖析了二者耦合关系的时空变化特征。结果显示:2003—2019年,东北地区综合城镇化水平提升了114.29%,总体呈现“东高西低”、辽中南城市群和哈长城市群核心城市引领全域发展的局面;资源环境承载力呈增加趋势,增幅36.09%,空间上聚集于哈大线周边区域;资源环境承载力水平与综合城镇化水平的耦合协调度总体上呈上升趋势,近年增幅有所下降,且辽西北、吉林南部和黑龙江西北部耦合协调度相对较低,核心城市和重要城市耦合协调度普遍较高。亟须提升核心城市对中小城镇的辐射引领能力,并加强生态退化地区的环境保护和高质量发展。

1990-2020年长三角地区生境质量与夜间灯光的空间关系

基于1990-2020年长三角地区的土地利用数据和夜间灯光数据,运用InVEST生境质量评估模型、双变量空间自相关、相关系数对生境质量与夜间灯光的时空关系进行研究,并应用地理加权回归和归纳法分析两者的响应规律,结果表明:(1)浙江省总体上生境最优且城镇发展最快,安徽省在城镇快速发展的同时生境相对下降最少,生境质量和夜间灯光空间分布格局呈现出与区位、地形等因素的空间耦合性。(2)长三角地区生境质量与夜间灯光指数随着时间的发展空间上的依赖性越来越强,聚类模式主要为高-低、低-高及低-低3种。高-低聚类区域主要分布在浙江省和安徽省的南部、西部的山地丘陵,研究期内呈现缩小的趋势;低-高聚类区域在长三角东部平原区呈集聚分布、北部平原丘陵区呈零散分布,呈现扩张趋势。(3)不同年份各省份生境质量与夜间灯光指数呈显著负相关,且经济越发达的省份,生境质量与夜间灯光指数的负相关关系越强;生境质量与夜间灯光指数呈高度负相关的区县主要分布在长江下游沿岸和浙江省东部,相关性不显著的区县主要分布在安徽省、江苏省的北部,变化类型以负相关关系持续增强型占比最高。(4)生境质量与夜间灯光指数的相关关系随着城市发展呈U型变化,即随着城市发展,生境质量与夜间灯光指数的负相关关系先增强后下降。研究结果可为长三角城市可持续发展、生境调控提供前期基础。

面向室内语音导航的“附近”关系协同定位方法

针对传统室内定位模式单一,且单一“附近”空间关系无法满足定位需求的问题,提出一种融合“附近”空间关系/无线保真(WiFi)/行人航迹推算(PDR)/地磁的室内定位方法:阐述多源融合语音交互室内定位方法框架;并针对室内环境,建立“附近”空间关系概率密度函数;然后步行构建地磁/WiFi指纹库;最后后通过“附近”空间关系约束粒子及指纹匹配空间范围,在PDR推算位置基础上,利用WiFi/地磁/“附近”空间关系更新粒子权重,实现最优位置估计。实验结果表明,基于粒子滤波融合单一“附近”空间关系/WiFi/PDR/地磁为一种低成本可行的定位方法,平均定位精度1.93 m,有90%可能性定位精度可达2.52 m。